On Empirical Likelihood Ratio Test for Equality of Means

by Aruna K. Rao and Aparna U.

Abstract:
In this paper, empirical likelihood ratio test is proposed for equality of means of two distributions. Simulation is carried out to check the adequacy of the chi-square approximation with one degree of freedom and F approximation with (1, ) degrees of freedom where m and n denote the sample sizes, to the null distribution of the test statistic. The proposed test is compared to the t-test and the Wilcoxon-Mann-Whitney test when the variances of the two populations are unknown but equal. The simulation results indicate that the empirical likelihood ratio test has marginally smaller power compared to the t-test when the underlying distribution is normal. The empirical likelihood ratio test emerges as the best when the distributions are logistic, uniform, log-normal and gamma.

On Empirical Likelihood Ratio Test for Equality of Means

by Aruna K. Rao and Aparna U.

Abstract:
In this paper, empirical likelihood ratio test is proposed for equality of means of two distributions. Simulation is carried out to check the adequacy of the chi-square approximation with one degree of freedom and F approximation with (1, ) degrees of freedom where m and n denote the sample sizes, to the null distribution of the test statistic. The proposed test is compared to the t-test and the Wilcoxon-Mann-Whitney test when the variances of the two populations are unknown but equal. The simulation results indicate that the empirical likelihood ratio test has marginally smaller power compared to the t-test when the underlying distribution is normal. The empirical likelihood ratio test emerges as the best when the distributions are logistic, uniform, log-normal and gamma.